Introduction to Python

Class Duration

• 35 hours of live online training
• Delivered over 5 days

Target Audience

• All students should have some experience with software development
• This is not an introduction to programming class
• Students should be familiar with common programming concepts such as variables, control flow, functions, arrays, etc.

Training Materials

All students receive comprehensive courseware covering all topics in the course. Courseware is distributed via GitHub in the form of documentation and extensive code samples. Students practice the topics covered through challenging hands-on lab exercises.

Software Requirements

Students will need a free, personal GitHub account to access the courseware. Students will need permission to install Python and Visual Studio Code on their computers. Also, students will need permission to install Python Packages and Visual Studio Code extensions. If students are unable to configure a local environment, a cloud-based environment can be provided.

Modern Python Tooling

• Installing Python 3.14 with uv (the modern, fast standard)
• uv for project setup, virtual environments, and dependency management
• ruff for formatting and linting
• VS Code with the Python and Pylance extensions
• Debugging Python in VS Code

Jupyter Notebooks

• Install and Configure Jupyter Notebooks (or use VS Code's notebook support)
• Run Jupyter Notebooks
• Edit and Run Cells
• Restarting the Kernel
• Configure Code Completion
• Debugging Python Code

Python Language

• Brief History
• Compared to Other Languages
• Common Uses
• Pythonic Programming
• PEP-8
• Indented Code Blocks
• Python 3.14 highlights: t-strings (PEP 750), better error messages, free-threaded build (now officially supported, PEP 779)

Types and Variables

• Static vs. Dynamic Typing
• Strong vs. Loose Typing
• Defining Variables
• Variable Scope
  • Built-In
  • Global
  • Non-Local
  • Local
• Naming Conventions
• Variable Metadata
  • Type function
  • Id function

Control-Flow

• If-Elif-Else Statement
• Match Statement
• While Loop
• For-In Loop
• Break
• Continue

Strings

• String Functions
• Formatting Strings
• Multiline Strings
• Raw Strings

Numbers

• Int vs Float
• Common Math Operations

Boolean

• Boolean Values
• Truthy/Falsy
• Comparison Expressions

Sequence Types

• What is a Sequence Type?
• Mutable vs. Immutable Sequences
• List Type
  • Create a List
  • Add/Remove Items from the List
  • List Functions
  • Slicing a List
  • Iterate over a List with Enumerate
  • Using Map and Filter with List
  • List Comprehensions
• Tuple Type
  • Create a Tuple
  • Tuples vs. Lists
  • Unpacking a Tuple
• Range Type
  • Start Index
  • End Index
  • Step Value

Map Type

• What is a Map Type?
• Dictionary Type
  • What is a key-value pair?
  • Create a Dictionary
  • Set a Value to a Key
  • Retrieve a Value with a Key
  • Handle a Key Error
  • Dictionary Functions
  • Iterate over a Dictionary

Dates and Times

• Date Time Module
• Time Module
• Parsing Dates
• Formatting Dates
• Handling Time Zones

Sorting

• In-Place Sorting
• Immutable Sorting
• Key Functions

Functions

• What is a Function?
• Functions as Objects
• Global, Non-Local, and Local Variables
• Parameters
• Positional vs. Keyword Arguments
• Default Parameter Values
• Lambda Functions
• Generators

Classes

• What is a Class?
• Define a Class
• Data Attributes
• Methods
• Basic Inheritance

Comments

• Commenting Python Code
• Doc Strings

Working with Data

• Opening and Closing Files
• Accessing Files through the Context Manager
• Download Data from an Http Server
• Read and Write CSV Files
• Read and Write JSON Files

Programming Scripts

• Program and Run Python Scripts outside of Jupyter Notebooks
• Printing Data to the Console
• Reading Data from the Console
• Configure Visual Studio Code for Python
• Code Linters and Formatters
• Organize Code into Modules